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A Risk-based Input-Output Methodology for Measuring the Effects of the August 2003 Northeast Blackout

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  • Christopher W. Anderson
  • Joost R. Santos
  • Yacov Y. Haimes

Abstract

The 2003 Northeast Blackout revealed vulnerabilities within the US electric power-grid system. With the economy so dependent on electric power for most aspects of life, a power-grid failure can have far-reaching higher-order effects and can impair the operability of other critical infrastructures. An inoperability of the power sector can result from different types of disasters (e.g., accidents, natural catastrophe, or willful attacks). This paper demonstrates the Inoperability Input-Output Model (IIM) to measure the financial and inoperability effects of the Northeast Blackout. The case study uses information from sources such as the US input-output tables and sector-specific reports to quantify losses for specific inoperability levels. The IIM estimated losses of the same magnitude as other published reports; however, with a detailed accounting of all affected economic sectors. Finally, a risk management framework is proposed to extend the IIM's capability for evaluating investment options in terms of their implementation costs and loss-reduction potentials.

Suggested Citation

  • Christopher W. Anderson & Joost R. Santos & Yacov Y. Haimes, 2007. "A Risk-based Input-Output Methodology for Measuring the Effects of the August 2003 Northeast Blackout," Economic Systems Research, Taylor & Francis Journals, vol. 19(2), pages 183-204.
    • Handle: RePEc:taf:ecsysr:v:19:y:2007:i:2:p:183-204
    DOI: 10.1080/09535310701330233
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    Citations

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    Cited by:

    1. Ali, Yousaf & Bilal, Muhammad & Sabir, Muhammad, 2021. "Impacts of transport strike on Pakistan economy: An inoperability Input-Output model (IIOM) approach," Research in Transportation Economics, Elsevier, vol. 90(C).
    2. Sellevåg, Stig Rune, 2021. "Changes in inoperability for interdependent industry sectors in Norway from 2012 to 2017," International Journal of Critical Infrastructure Protection, Elsevier, vol. 32(C).
    3. Abrate, Graziano & Bruno, Clementina & Erbetta, Fabrizio & Fraquelli, Giovanni & Lorite-Espejo, Azahara, 2016. "A choice experiment on the willingness of households to accept power outages," Utilities Policy, Elsevier, vol. 43(PB), pages 151-164.
    4. Faramondi, Luca & Oliva, Gabriele & Setola, Roberto, 2020. "Multi-criteria node criticality assessment framework for critical infrastructure networks," International Journal of Critical Infrastructure Protection, Elsevier, vol. 28(C).
    5. Arnaud Mignan & Ziqi Wang, 2020. "Exploring the Space of Possibilities in Cascading Disasters with Catastrophe Dynamics," IJERPH, MDPI, vol. 17(19), pages 1-21, October.
    6. Barker, Kash & Haimes, Yacov Y., 2009. "Assessing uncertainty in extreme events: Applications to risk-based decision making in interdependent infrastructure sectors," Reliability Engineering and System Safety, Elsevier, vol. 94(4), pages 819-829.
    7. Gu, Chenghong & Zhang, Xin & Ma, Kang & Yan, Jie & Song, Yonghua, 2018. "Impact analysis of electricity supply unreliability to interdependent economic sectors by an economic-technical approach," Renewable Energy, Elsevier, vol. 122(C), pages 108-117.
    8. Henriet, Fanny & Hallegatte, Stéphane & Tabourier, Lionel, 2012. "Firm-network characteristics and economic robustness to natural disasters," Journal of Economic Dynamics and Control, Elsevier, vol. 36(1), pages 150-167.
    9. Botelho, Vinícius, 2019. "Estimating the economic impacts of power supply interruptions," Energy Economics, Elsevier, vol. 80(C), pages 983-994.
    10. Ouyang, Min, 2014. "Review on modeling and simulation of interdependent critical infrastructure systems," Reliability Engineering and System Safety, Elsevier, vol. 121(C), pages 43-60.
    11. Barker, Kash & Santos, Joost R., 2010. "Measuring the efficacy of inventory with a dynamic input-output model," International Journal of Production Economics, Elsevier, vol. 126(1), pages 130-143, July.
    12. Mohamad Darayi & Kash Barker & Joost R. Santos, 2017. "Component Importance Measures for Multi-Industry Vulnerability of a Freight Transportation Network," Networks and Spatial Economics, Springer, vol. 17(4), pages 1111-1136, December.
    13. Chen, Hao & Yan, Haobo & Gong, Kai & Geng, Haopeng & Yuan, Xiao-Chen, 2022. "Assessing the business interruption costs from power outages in China," Energy Economics, Elsevier, vol. 105(C).
    14. Oosterhaven, Jan, 2015. "On the doubtful usability of the inoperability IO model," Research Report 15008-EEF, University of Groningen, Research Institute SOM (Systems, Organisations and Management).
    15. Clementina Bruno & Ugo Finardi & Azahara Lorite-Espejo & Elena Ragazzi, 2016. "Emerging costs deriving from blackouts for individual firms: evidence from an Italian case study," quaderni IRCrES 201601, CNR-IRCrES Research Institute on Sustainable Economic Growth - Moncalieri (TO) ITALY - former Institute for Economic Research on Firms and Growth - Torino (TO) ITALY.
    16. Sara Meerow & Joshua P. Newell, 2015. "Resilience and Complexity: A Bibliometric Review and Prospects for Industrial Ecology," Journal of Industrial Ecology, Yale University, vol. 19(2), pages 236-251, April.
    17. Stéphane Hallegatte, 2012. "Modeling the roles of heterogeneity, substitution, and inventories in the assessment of natural disaster economic costs," Post-Print hal-00802050, HAL.
    18. Chopra, Shauhrat S. & Khanna, Vikas, 2015. "Interconnectedness and interdependencies of critical infrastructures in the US economy: Implications for resilience," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 436(C), pages 865-877.
    19. He, Peijun & Ng, Tsan Sheng & Su, Bin, 2017. "Energy-economic recovery resilience with Input-Output linear programming models," Energy Economics, Elsevier, vol. 68(C), pages 177-191.
    20. Rui Huang & Arunima Malik & Manfred Lenzen & Yutong Jin & Yafei Wang & Futu Faturay & Zhiyi Zhu, 2022. "Supply-chain impacts of Sichuan earthquake: a case study using disaster input–output analysis," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 110(3), pages 2227-2248, February.
    21. Pagani, Giuliano Andrea & Aiello, Marco, 2014. "Power grid complex network evolutions for the smart grid," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 396(C), pages 248-266.

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